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Dutton, A. and Carlson, A.E. and Long, A.J. and Milne, G.A. and Clark, P.U. and DeConto, R. and Horton,B.P. and Rahmstorf, S. and Raymo, M.E. (2015) 'Sea-level rise due to polar ice-sheet mass loss during pastwarm periods.', Science., 349 (6244). aaa4019.

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Title: Sea-level rise due to polar ice-sheet mass loss during past warm periods

Authors: A. Dutton1*, A. E. Carlson2, A. J. Long3, G. A. Milne4, P. U. Clark2, R. DeConto5, B. P. Horton6,7, S. Rahmstorf8, M. E. Raymo9 1 Department of Geological Sciences, University of Florida, USA. 2 College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, USA. 3 Department of Geography, Durham University, UK. 4 Department of Earth Sciences, University of Ottawa, Canada. 5 Department of Geosciences, University of Massachusetts, USA. 6 Department of Marine and Coastal Sciences, Rutgers University, USA. 7 Earth Observatory of Singapore, Nanyang Technological University, Singapore. 8 Potsdam Institute for Climate Impact Research, Germany. 9 Lamont-Doherty Earth Observatory, Columbia University, USA.

*Correspondence to: adutton@ufl.edu

1-pg SUMMARY: Background Although thermal expansion of seawater and melting of mountain glaciers has dominated global mean sea level (GMSL) rise over the last century, mass loss from the Greenland and Antarctic ice sheets is expected to exceed other contributions to GMSL rise under future warming. To better constrain polar ice-sheet response to warmer temperatures, we draw upon evidence from interglacial periods in the geologic record that experienced warmer polar temperatures and higher GMSLs than present. Coastal records of sea level from these previous warm periods demonstrate geographic variability due to the influence of several geophysical processes that operate across a range of magnitudes and timescales. Inferring GMSL and, thus, ice-volume changes from these reconstructions is non-trivial and generally requires the use of geophysical models. Advances Interdisciplinary studies of geologic archives have ushered in a new era of deciphering magnitudes, rates and sources of sea-level rise. Advances in our understanding of polar ice-sheet response to warmer climates have been made through an increase in the number and geographic distribution of sea-level reconstructions, better ice-sheet constraints, and the recognition that several geophysical processes cause spatially complex patterns in sea level. In particular, accounting for glacial isostatic processes helps to decipher spatial variability in coastal sea-level records and has reconciled a number of site-specific sea-level reconstructions for warm periods that have occurred within the past several hundred thousand years. This enables us to infer that during recent interglacial periods, small

increases in global mean temperature and just a few degrees of polar warming relative to the pre-Industrial period resulted in ≥6 meters of GMSL rise. Mantle-driven dynamic topography introduces large uncertainties on longer timescales, affecting reconstructions for time periods such as the Pliocene (~3 million years ago), when atmospheric CO2 was ~400 ppm, similar to that of the present. Both modeling and field evidence suggest that polar ice sheets were smaller during this time period, but because dynamic topography can cause tens of meters of vertical displacement of at the Earth’s surface on million-year timescales and uncertainty in model predictions of this signal are large, it is currently not possible to make a precise estimate of peak GMSL during the Pliocene. Outlook Our present climate is warming to a level associated with significant polar ice-sheet loss in the past, but a number of challenges remain to further constrain ice-sheet sensitivity to climate change using paleo-sea level records. Improving our understanding of rates of GMSL rise due to polar ice-mass loss is perhaps the most societally relevant information the paleo record can provide, yet robust estimates of rates of GMSL rise associated with polar ice-sheet retreat and/or collapse remain a weakness in existing sea-level reconstructions. Improving existing magnitudes, rates, and sources of GMSL rise will require a better (global) distribution of sea-level reconstructions with high temporal resolution and precise elevations, and should include sites close to present and former ice sheets. Translating such sea-level data into a robust GMSL signal demands integration with geophysical models, which in turn can be tested through improved spatial and temporal sampling of coastal records.

Further development is needed to refine estimates of past sea level from geochemical proxies. In particular, paired oxygen isotope and Mg/Ca data are currently unable to provide confident, quantitative estimates of peak sea level during these past warm periods. In some GMSL reconstructions, polar ice-sheet retreat is inferred from the total GMSL budget, but identifying the specific ice-sheet sources is currently hindered by limited field evidence at high latitudes. Given the paucity of such data, emerging geochemical and geophysical techniques show promise for identifying the sectors of the ice sheets that were most vulnerable to collapse in the past and perhaps will be again in the future.

Figure 1.

Peak global mean temperature, atmospheric CO2, maximum global mean sea level

(GMSL), and source(s) of meltwater. Light blue shading indicates uncertainty of GMSL

maximum. Red pie charts over Greenland and Antarctica denote fraction (not location) of

ice retreat.

Title: Sea-level rise due to polar ice-sheet mass loss during past warm periods

Authors: A. Dutton1*, A. E. Carlson2, A. J. Long3, G. A. Milne4, P. U. Clark2, R. DeConto5, B. P. Horton6,7, S. Rahmstorf8, M. E. Raymo9 1 Department of Geological Sciences, University of Florida, USA. 2 College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, USA. 3 Department of Geography, Durham University, UK. 4 Department of Earth Sciences, University of Ottawa, Canada. 5 Department of Geosciences, University of Massachusetts, USA. 6 Department of Marine and Coastal Sciences, Rutgers University, USA. 7 Earth Observatory of Singapore, Nanyang Technological University, Singapore. 8 Potsdam Institute for Climate Impact Research, Germany. 9 Lamont-Doherty Earth Observatory, Columbia University, USA.

*Correspondence to: adutton@ufl.edu

Abstract:

Interdisciplinary studies of geologic archives have ushered in a new era of deciphering

magnitudes, rates and sources of sea-level rise from polar ice-sheet loss during past warm

periods. Accounting for glacial isostatic processes helps to reconcile spatial variability in

peak sea level during Marine Isotope Stages (MIS) 5e and 11, when the global mean

reached 6-9 m and 6-13 m higher than present, respectively. Dynamic topography

introduces large uncertainties on longer timescales, precluding robust sea-level estimates

for intervals such as the Pliocene. Present climate is warming to a level associated with

significant polar ice-sheet loss in the past. Here we outline advances and challenges

involved in constraining ice-sheet sensitivity to climate change using paleo-sea level

records.

One sentence summary: Advances in reconstructions of past sea level reveal high

sensitivity of polar ice sheets to small warming.

Main text:

Global mean sea level (GMSL) has risen over the past century largely in response to

global warming (~0.19 m rise in GMSL between 1901 and 2010) (1). The response to

global warming includes thermal expansion of ocean water as well as mass loss from

glaciers and ice sheets, all of which increase the volume of water in the ocean and, thus,

cause a sea-level rise. Recent GMSL rise has been dominated by thermal expansion and

glacier loss, which collectively explain ~75% of the observed rise since 1971 (1). The

contribution from mass loss from the Greenland (GrIS) and Antarctic (AIS) ice sheets has

increased since the early 1990s, comprising ~19% of the total observed rise in GMSL

between 1993-2010 (1), and is expected to exceed other contributions under future

sustained warming (e.g., 2). Estimates from short, recent time periods—though not as

robust as analyses of longer records due to the dominance of interannual variability—

suggest that polar ice-sheet loss may now comprise as much as ~40% of the total observed

rise in GMSL between 2003-2008 (3, 4).

These same processes contributed to higher-than-present sea levels in the past

when global mean temperature was warmer than the pre-Industrial period (before 1750).

However, because mountain glaciers and thermal expansion can only explain ~1-1.5 m of

GMSL rise for the 1-3 °C warming associated with these periods (5, 6), evidence for former

GMSL exceeding this amount requires a contribution from the GrIS and/or AIS.

Understanding how polar ice sheets lost mass and contributed to sea-level rise during past

warm periods can provide insights into their sensitivity to climate change as well as

constrain process-based models used to project ice-sheet response to future climate

change.

Many studies have used data and/or models to determine the sensitivity of ice

sheets to changes in temperature or atmospheric CO2 over long timescales (2, 7-12). Given

the recent increases in greenhouse gases (GHGs) and global mean temperature, the present

ice sheets are out of equilibrium with the climate, raising important questions regarding

their potential future contribution to sea-level rise: (i) What is the equilibrium sea-level

rise for a given warming scenario? (ii) How quickly will the GrIS and AIS respond to

present and future radiative forcing and associated warming and what will be the

accompanying rates of sea-level change? (iii) What are the source regions of the ice-mass

loss, a factor that will strongly influence the geographic pattern of future sea-level change

(1, 2, 13)?

To address these questions, we examine how our understanding of ice-sheet

response during past warm periods is evolving through the progressive integration of

several disciplines. In particular, we consider observational evidence of paleo sea levels

and ice-sheet reconstructions, with climate, ice-sheet, and solid Earth models. For each

time period, we identify key geophysical signals that must be quantitatively estimated and

removed from relative sea level (RSL; refers to the local height of sea level) records in

order to infer past changes in GMSL (Text Box 1). Finally, we review the state of knowledge

regarding the magnitudes, rates, and sources of sea-level rise during several of the most

prominent interglacial peaks of the last three million years, including the Mid-Pliocene

warm period (MPWP, ~ 3 million years ago), MIS 11 (~400 thousand years ago (ka)), and

MIS 5e (~125 ka) (Fig. 1).

Mid-Pliocene Warm Period (~3.2 to 3.0 million years ago)

The MPWP comprises a series of orbitally paced (41-thousand year (ky)) climate

cycles associated with atmospheric CO2 in the range of 350-450 ppm (14, 15). Peak global

mean temperatures derived from general circulation model simulations average 1.9-3.6 °C

warmer than pre-Industrial (16). Some Arctic temperature reconstructions indicate

warming of 8 °C or more while some Southern Ocean records suggest warming of 1-3 °C

(17). However, these temperature estimates are uncertain and, in some cases, may not

correlate precisely to the MPWP time interval. Both modeling and field evidence suggest

that polar ice sheets were smaller during the MPWP, but constraints on the magnitude of

GMSL maxima during the warm extremes as inferred from RSL reconstructions are highly

uncertain (18).

In the Southern Hemisphere, the West Antarctic Ice Sheet (WAIS) experienced

multiple retreat and advance phases during the Pliocene (19). Studies of ice-rafted debris

(IRD) suggest that portions of the East Antarctic Ice Sheet (EAIS) experienced retreat

during parts of the early to middle Pliocene (20), apparently paced by precessional (23-

kyr) cycles (21). In the Northern Hemisphere, there are no firm observational constraints

on changes in the size of the MPWP GrIS. Ice-sheet models, on the other hand, simulate

retreat in both Greenland (22) and Antarctica (12) in response to imposed Pliocene climate

forcing, raising GMSL by ~7 m and ~6 m, respectively.

Many early studies of Pliocene coastal records considered the Earth to be rigid and

thus, inferred a uniform GMSL rise across a wide range of elevations (+15-60 m, see Table 1

in (18)). Some studies attempted to correct individual RSL records for the influence of local

tectonics or subsidence (23-27). More recently, Raymo et al. (18) corrected Pliocene RSL

observations for the effects of GIA, but the global variability in the elevation of observed

shorelines remains substantial, ranging over tens of meters. This is thought to be due to the

influence of dynamic topography, as well as to uncertainties in the elevation and age of the

shoreline features (18, 28, 29). Improvements in model parameters for GIA and dynamic

topography and in dating of coastal records are thus needed to better constrain estimates

of Pliocene sea level from coastal records.

The amplitude of negative excursions in benthic 18O records during the MPWP

(~0.4‰ relative to the Holocene) (Fig. 1) may imply higher GMSL than today, but

extracting the ice-volume signal from the 18O calcite record remains a challenge. Typical

analytical errors in 18O measurements translate to large uncertainties in sea level (~ ±10

m). Moreover, inferring ice volume requires that the contribution of seawater temperature

and hydrography to the benthic 18O signal is known. The Mg/Ca of the benthic calcite

record can be used to isolate the temperature portion of the corresponding 18O signal, but

uncertainties in calibration (30, 31), carbonate ion saturation (32), diagenesis of calcite

(33), and long-term seawater Mg/Ca variability (34) are significant. Until these effects are

better understood and able to be isolated, the 18O proxy records will continue to be

plagued by errors as large as the signal we are seeking. In light of these considerations, the

Miller et al. (24) peak GMSL estimate of 21 ± 10 m at the end of the MPWP (~2.95 Ma) that

is based on evidence from non-GIA corrected coastal records, benthic 18O (35), and paired

18O-Mg/Ca records probably carries more uncertainty than the quoted range.

Marine isotope stage 11 (~424,000-395,000 years ago)

Marine isotope stage (MIS) 11 was an unusually long interglacial period (~30 kyr)

with a highly uncertain global average temperature (estimates range from slightly cooler

than MIS 5e (see below) (36, 37) up to ~2 °C warmer than pre-Industrial (38)) and

atmospheric CO2 peaking at 286 ppm (similar to pre-Industrial values) (39). Limited proxy

data indicate Arctic summer maximum air and sea surface temperatures reaching up to 4

and 9 °C warmer, respectively, than peaks attained during MIS 1 or 5e (40, 41). Antarctic

ice-core analyses indicate temperatures ~2.6 °C warmer than pre-Industrial (42). Climate

models forced by insolation and GHG concentrations during MIS 11, however, simulate only

slightly warmer global mean temperatures (~0.1 °C) than for MIS 1 (38, 43). Hence, if the

limited proxy data are correct in implying enhanced warmth in the polar regions, the

underlying cause of the warmer climates is unresolved.

Reconstructions of MIS 11 GMSL suggest that it was higher than present. Several

records document at least partial retreat of the GrIS during MIS 11, suggesting it

contributed to higher GMSL. Pollen in marine records offshore of southeast Greenland

indicate the development of spruce forest over parts of now-ice-covered regions (44).

Likewise, biomolecules from the base of the Dye-3 ice core indicate a forested southern

Greenland that could be from MIS 11, although the age of these molecules is uncertain (45).

A cessation of ice-sheet eroded sediment discharge and IRD suggests ice-margin retreat

from the southern Greenland coast (46), whereas continued IRD deposition in the

northeast demonstrates the persistence of marine-terminating ice over northeastern

Greenland (47). Comparison of these constraints with ice-sheet models suggests that the

GrIS could have contributed 4.5-6 m to GMSL rise above present (46). Higher GMSL

estimates thus require an Antarctic contribution, but few geologic constraints on AIS

history exist for MIS 11 (48).

Early work on interpreting MIS 11 coastal records assumed a geographically

uniform GMSL change, with sea-level estimates ranging from -3 m (49) to +20 m (50). If the

records are all the same age, the large range may largely reflect geographic variability in

the RSL signal associated with GIA and dynamic topography (Box 1). For example, when

corrected for GIA, MIS 11 RSL in the Bermuda and Bahamas regions (~20 m above present)

suggests a peak GMSL of only 6-13 m above present (51), a level that would require loss of

the GrIS and/or sectors of the AIS. This estimate is consistent with the 8-11.5 m estimate

based on paleoshorelines in South Africa that have been corrected for GIA effects and local

tectonic motion (52, 53). Overall, multiple lines of evidence would seem to agree that GMSL

was 6-13 m higher near the end of MIS 11.

By comparison, paired 18O – Mg/Ca measurements of benthic foraminifera suggest

GMSL during MIS 11 in excess of 50 ± ~20 m above present (31, 54), although as with the

MPWP reconstructions, the uncertainties on these estimates may be much larger. On the

other hand, the Red Sea planktic 18O record suggests RSL reached just above present (1 ±

12 m at 2) (55, 56). Additional contributions from GIA and possibly also from dynamic

topography to the sill depth of the Red Sea over the last several hundred kyr that are not

captured in the present reconstruction could impart additional uncertainties. The large

uncertainty and lack of agreement associated with all of these 18O-based records points to

the difficulty in using them to tightly constrain peak GMSL during previous warm periods.

Marine isotope stage 5e (~129,000–116,000 years ago)

We consider the time interval of MIS 5e when GMSL was above present (~129-116

ka) (8, 57). Relative to the pre-Industrial period, model simulations indicate little global

average temperature change during MIS 5e, while proxy data imply ~1 °C of warming, but

with possible spatial and temporal sampling biases (58). Greenland temperatures peaked

between ~5-8 °C above pre-Industrial (59, 60) and Antarctic temperatures were ~3-5 °C

warmer (42).

Shorelines that developed during the MIS 5e sea-level highstand are the best-

preserved and most geographically widespread record of a higher-than-present GMSL

during a previous warm period. Recent global compilations of RSL data combined with GIA

modeling indicate that peak GMSL was higher than the previous long-standing estimate (4-

6 m), in the range of ~6-9 m above present (61, 62), in agreement with site-specific, GIA-

corrected coastal records in the Seychelles at 7.6 ± 1.7 m (63) and in Western Australia at 9

m (no uncertainty reported) (64) above present (Fig. 3). The Red Sea planktic 18O record

places peak RSL values during MIS 5e at 6.7 ± 3.4 m (maximum probability with 95%

probability envelope) (65). Detailed GIA corrections for the temporal evolution of the

hydraulic geometry of the Red Sea during MIS 5e are not applied to this planktic 18O

record, and could change the peak value by a few meters (66). Paired benthic 18O-Mg/Ca

data (31, 54) reflect high uncertainty and poor agreement for peak GMSL when compared

to the coastal records (Fig. 4).

The 3 m uncertainty range in peak GMSL derived from coastal records (i.e., ~6-9 m)

presents a challenge when assessing relative GrIS and AIS contributions. Ice-core and

marine records show that the GrIS was smaller than present during MIS 5e, with

substantial (but not complete) retreat of the southern sector at the same time as peak

GMSL ~122-119 ka (60, 67). Recent modeling studies suggest that total GrIS mass loss was

between 0.6-3.5 m (Fig. 3, and references therein). With thermal expansion and melting of

mountain glaciers contributing up to ~1 m rise (5, 68), an additional contribution is

required from the AIS to explain peak GMSL during MIS 5e. However, direct evidence for

AIS retreat at this time is lacking, with only some poorly dated records that suggest that

WAIS retreated during some previous interglacial periods, including possibly MIS 5e (69).

The primary means of establishing an accurate and precise chronology for MIS 5e

sea level is through U-Th dating of fossil corals that lived near the sea surface. Existing

chronologies suggest regional differences in the timing of peak MIS 5e RSL. In some cases,

this reflects variable diagenesis that causes open-system conditions in the corals with

respect to U and Th isotopes (e.g., 70). However, differences in timing may also be real and

reflect the spatially variable influence of GIA (61). Most studies suggest that peak GMSL

occurred sometime after ~125 ka, usually in the range of ~122-119 ka (64, 71-74), but the

timing of AIS versus GrIS contributions to maximum GMSL remains unresolved.

Differences in RSL reconstructions from site to site yield a range of interpretations

about the evolution of GMSL during the MIS 5e highstand, including: (i) a stable sea level

(57); (ii) two peaks separated by an ephemeral drop in sea level (72, 73); (iii) a stable sea

level followed by a rapid sea-level rise (64, 71); and (iv) three to four peaks in sea level

reflecting repeated sea-level oscillations (74, 75). As yet, no consensus exists regarding this

suite of scenarios, but robust sedimentary evidence from multiple coastal sites argues for

at least one and possibly several meter-scale sea-level oscillations during the course of the

highstand (e.g., 64, 71, 72, 73, 76). These data suggest dynamic behavior of polar ice sheets

at a time when global mean temperature was similar to present. It is not clear whether

such variability was driven by one unstable ice-sheet sector or by differences in the

phasing of ice-mass changes in multiple ice-sheet sectors across the duration of MIS 5e.

Estimated rates of sea-level change associated with these oscillations range from 1-

7 m kyr-1 (74, 75, 77). Resolving rates on shorter timescales is hindered by the precision of

the dating and RSL reconstruction methods. Even the m kyr-1 rates listed above are highly

uncertain if one incorporates a full consideration of observational errors. For example, MIS

5e reefs in the Bahamas have uncertainties in coral paleo-water depths of >5 m (based on

the assumed depth range of Acropora palmata) or more (for the Montastrea sp. and Diploria

sp.), which are similar in magnitude to the inferred change in sea level (4-6 m) (72, 74). As

another example, meter-scale RSL fluctuations during the MIS 5e highstand inferred from

the Red Sea planktic 18O record are not replicated between the two cores used in the

analysis and the variability largely falls within the reported uncertainty, so it is not possible

to reject the null hypothesis that RSL was stable based on this record (75). Thus, despite

the clear sedimentary evidence for sea-level variability in during MIS 5e, associated rates of

GMSL change remain poorly resolved.

The Holocene (11,700 years ago to present)

Global mean temperatures during the Holocene have ranged from ~0.75 °C warmer

(from ~9.5-5.5 ka) than pre-Industrial temperatures (78) to pre-Industrial levels (79).

While this temperature reconstruction is relatively well constrained by proxy data, we note

that models simulate a warming trend through the Holocene, which may be an indication of

uncertainty in the reconstructions, the models, or both (80).

The Holocene has the most abundant and highly resolved RSL reconstructions in

comparison to previous interglacial periods (Fig. 2). In addition, the history of ice-sheet

retreat is relatively well constrained, particularly in the Northern Hemisphere. Detailed

sea-level reconstructions from the last few millennia are important for constraining the

natural variability in sea level and, thus, providing context for evaluating current and

future change (1, 81).

GMSL was ~60 m lower than present at the beginning of the Holocene, due largely

to the remaining Scandinavian and Laurentide ice sheets as well as a greater-than-present

AIS volume. Rates of GMSL rise slowed by ~7 ka following the final deglaciation of the

Laurentide Ice Sheet—from ~15 m kyr-1 between ~11.4-8.2 ka to ~1 m kyr-1 or less for the

remainder of the pre-Industrial Holocene (82). Only a few meters of ice-sheet loss occurred

between ~7 and ~2 ka (82, 83), which is thought to be dominated by loss from the AIS (84,

85). Field data and ice-sheet models suggest that the GrIS was smaller than present during

the early to middle Holocene thermal optimum (9.5-5.5 ka) (86, 87), and began to re-

advance during the cooler Neoglacial period (<5 ka), reaching its maximum extent in many

places during the Little Ice Age and causing a GMSL lowering of <0.2 m (88).

Over the last ~7 kyr, RSL has fallen in many near-field areas that were formerly

covered by major ice sheets because of glacial isostatic rebound (Fig. 2a), while RSL in

intermediate- and far-field regions reflects changes in GMSL, proglacial forebulge collapse,

and hydro-isostatic loading (89, 90), with deltaic regions being further influenced by

compaction (Fig. 2b-d). Equatorial and Southern Hemisphere RSL reconstructions record a

mid-Holocene highstand at ~6 ka of a few decimeters to several meters (91, 92) (Fig. 2e-h)

that is a consequence of the GIA effect known as equatorial siphoning (89, 90).

Sea-level reconstructions from salt marshes bordering the North Atlantic region

reveal regional decimeter-scale variability on multi-decadal to millennial timescales over

the last ~2 ka (93, 94) (Fig. 2i) that reflect ice-sheet loss and coupled atmosphere-ocean

variability (95). Late-Holocene ice-margin reconstructions for the AIS suggest little change

(84, 85, 96), while those for the GrIS suggest general advance (86-88). The clearest signal in

geological and long tide gauge records is the transition from low rates of change during the

last ~2 ka (order tenths of mm yr-1) to modern rates (order mm yr-1) in the late 19th to

early 20th centuries, although the spatial manifestation of this change is variable (1, 81).

Discussion and Future Challenges

Recent interdisciplinary studies on sea-level and ice-sheet change during previous

warm periods confirm that there is a strong sensitivity of polar ice-sheet mass loss (and

associated sea-level rise) to higher insolation forcing and polar temperatures and similar

or higher GHG forcing (Fig. 4). This understanding of polar ice-sheet response to climate

change has improved considerably through an increase in the number and geographic

distribution of RSL reconstructions, better ice-sheet constraints, and the recognition that

several geophysical processes cause spatially complex patterns across timescales spanning

tens to millions of years (Figs. 1-2). Spatial variability in Holocene RSL from GIA has long

been recognized (89), but widely disparate estimates of the magnitude of GMSL change

associated with any given previous warm period have only recently been documented as

similarly reflecting the spatial variability in RSL resulting from GIA and dynamic

topography (e.g., see MIS 5e estimates in Fig. 3).

Despite the many advances in our understanding of GMSL during past warm

periods, a number of challenges remain. Foremost among these is the need to continue to

improve the accuracy and precision of the age and elevation of RSL indicators. In particular,

now that we recognize that time-dependent GIA effects will affect the elevation of

shorelines depending on whether they formed early or late in the interglacial period,

improving chronologies to resolve the timing of observations during RSL highstands

becomes all that much more critical to inferring the GMSL signal (51, 61). Although the

precision of U-Th dating has improved, complications related to open-system diagenesis

and former seawater U-isotope composition continue to limit precision and accuracy of

marine carbonate U-Th ages (see review by 97).

Translating site-specific data into a global context requires better constraints on the

properties of the solid Earth that strongly influence RSL on long timescales, especially the

viscosity and density structure of the mantle. Increased spatial and temporal density of

past RSL and ice-sheet margins will improve ice and Earth models, while use of 3-D GIA

models may improve predictions in areas where lateral heterogeneities are important (98).

Determining equilibrium GMSL for different forcing scenarios using paleo data

requires consideration of factors beyond understanding the peak value of GMSL, polar (or

global) temperature, or atmospheric CO2 during a given time period. Given lags in the

climate system, simple correlation between such climate parameters can be misleading

because the extremes may not be synchronous over a 10-kyr long interglacial period. Peak

temperatures attained during previous warm periods may also be dependent upon the

length of the interglacial period (41, 46), suggesting that warm periods lasting several kyr

may not represent equilibrium conditions for the climate-cryosphere system. Moreover, ice

sheets in different hemispheres may not respond in phase.

In the case of MIS 11 and 5e, warm climates and higher GMSL resulted largely from

orbital forcing that changes the intensity of solar insolation at high latitudes. Insolation

forcing is quite different from the relatively uniform global forcing of increased

atmospheric CO2 that will influence future sea levels. Furthermore, regional sea and air

temperatures exert the most direct influence on mass loss from a polar ice sheet,

suggesting that past global mean temperature may not be the best predictor for past GMSL.

More detailed regional climate reconstructions thus represent an additional target to

improve understanding of the climatic forcing required for specific ice-sheet response

scenarios. Improved chronological frameworks are also required that can directly relate

sea-level and climate reconstructions, particularly to facilitate comparisons between

reconstructions that rely on radiometric versus orbitally tuned chronologies.

In the following, we summarize our current understanding of magnitudes, rates, and

sources of sea-level change during warm periods and their associated uncertainties, and

conclude with the recommendation to develop comprehensive databases that will be

required to optimally capture the temporal and spatial variability of past high sea levels

and their sources.

Magnitudes of GMSL Rise: The best agreement in the magnitude of peak GMSL is between

multiple GIA-corrected coastal records for MIS 5e and 11, but the uncertainty introduced

from the combined influence of GIA and dynamic topography going farther back in time

presently precludes us from placing a firm estimate on GMSL during the MPWP interglacial

peaks. Given the constraints from existing data and models of MPWP temperatures and ice-

sheet reconstructions combined with the evidence for stronger GHG forcing, we

hypothesize that MPWP sea levels would have exceeded those attained during MIS 11 and

5e. This provides a lower bound of +6 m with the distinct potential for higher GMSL,

particularly if the GrIS, WAIS, and EAIS experienced simultaneous mass loss. This

hypothesis should be tested in the context of additional data and modeling constraints.

In comparison to GIA-corrected coastal records, paired 18O-Mg/Ca records have

greater uncertainty, and in several cases have poor accuracy, suggesting that the current

state of these geochemical methods makes them unable to provide confident, quantitative

estimates of peak GMSL during these periods (Fig. 4). The planktic 18O from the Red Sea

(15, 75, 84) is an innovative approach to overcoming some of the limitations of the benthic

18O or paired 18O-Mg/Ca methods and remains one of the most valuable, semi-continuous

records of sea-level change across century to millennial timescales. However, it carries

uncertainties that are common to both the coastal reconstructions (such as GIA

corrections) as well as the other 18O-based reconstructions, some of which will magnify

farther back in time. Targeted GIA modeling of the Red Sea basin, in particular to derive

isostatic corrections for the Hanish Sill during these interglacial highstands, would be a

valuable undertaking towards using this reconstruction to interpret GMSL.

Rates of GMSL Rise: Rates of sea-level change for previous warm periods when sea level

was higher than present range from highly uncertain to completely unconstrained

depending on the time period, yet this is perhaps the most societally relevant information

the paleo record can provide for predicting and adapting to future sea-level change. MIS 5e

holds the greatest potential for information on past rates of sea-level change in a world

with higher GMSL. While MIS 5e sea-level oscillations appear abrupt in the sedimentary

record, uncertainties in dating and interpretation of RSL markers have prevented precise

quantification of this abruptness beyond an indication that GMSL rose (and fell) one to

several meters over one to a few kyr (e.g., 74). Hence, deriving rates of interest on societal

timescales (cm yr-1, m century-1), such as can be achieved in Holocene reconstructions,

remains a primary challenge.

Resolving meter-scale sea-level variability during the MIS 5e highstand will require

precise chronologies and stratigraphy of sea-level indicators as well as improved precision

in the vertical uncertainties of RSL indicators. Coastal geomorphological features, while

compelling, are difficult to date. Fossil corals can potentially provide robust chronologies, if

challenges associated with the interpretation of post-depositional alteration of U-Th

isotope measurements can be overcome (97). Further, fossil corals are usually associated

with significant vertical uncertainties in their paleowater depth. Future improvements on

existing paleowater depth estimates of fossil corals will require integration of

paleoenvironmental information, including assemblages of reef biota, and a more

quantitative understanding of the depth distribution of modern corals and associated reef

biota (99).

The rate of GMSL rise associated Northern Hemisphere ice-sheet retreat during the

last deglaciation is often cited as providing an upper bound for potential future GMSL rise

(e.g., >4 m century-1 during meltwater pulse 1A: 100). The nature and forcing of that

retreat, however, is expected to be significantly different to that of the warm-climate polar

ice sheets and thus not directly analogous. Nevertheless, there are aspects of past sea-level

changes during glacial maxima or during deglacial transitions that are relevant to

understanding interglacial GMSL change. For example, recent modeling identified a

identified a positive feedback involving ‘saddle collapse’ of the Laurentide Ice Sheet melting

that is capable of delivering a substantial influx of meltwater as a possible mechanism

contributing to MWP-1A (101). Saddle collapse between the southern and northern domes

of the GrIS may be important for driving smaller scale, but rapid GMSL change during warm

interglacial periods. Similarly, there is increasing evidence that ocean thermal forcing

played an important role in destabilizing late-Pleistocene ice sheets (e.g., 102), similar to

what is projected for the future.

Constraining the total volume and geographic extent of grounded ice during the Last

Glacial Maximum (LGM), in particular, is an important parameter for GIA model predictions

of RSL across all time periods, including the present and past interglacial periods (e.g., 18).

Improved constraints on LGM ice volume will also influence the quantification of GMSL

changes based on benthic 18O reconstructions as well as paired 18O-Mg/Ca

reconstructions. However, there are presently few far-field sites with RSL histories that can

be used to constrain the LGM. We note that an ~120 m-below-present GMSL during the

LGM has long been held as conventional wisdom, yet several recent (and some earlier) GIA

studies put the estimate in the range of 130-134 m below present (Fig. S1). Because the

total volume and extent of the LGM ice sheets is a sensitive parameter for GIA model

predictions, improving our understanding of glacial ice loads will influence our

interpretations of rates and magnitudes of interglacial GMSL.

Sources of GMSL Rise: Two approaches show great promise for identifying and quantifying

the contribution of individual ice sheets that retreated during previous warm periods:

geochemical provenance in marine sediments (20, 46, 67) and sea-level fingerprinting

(103). Existing evidence points to southern Greenland as the most susceptible sector of the

GrIS to warmer-than-present temperatures (46, 67), although some models predict retreat

in the north and others in the south. In Antarctica, compelling sedimentary (19, 21) and

modeling (12, 104) evidence suggests that repeated retreat-advance cycles of the WAIS

occurred during the Pliocene and early Pleistocene, but little direct evidence constrains

changes in the AIS during more recent intervals, including MIS 11 and 5e and the Holocene.

Marine-based portions of the EAIS may be just as vulnerable as the WAIS and should be

equally considered as contributors to past sea-level change (105).

Improving our understanding of individual polar ice-sheet contributions to GMSL is

a key challenge. An important uncertainty for future projections of the GrIS is the threshold

temperature beyond which it undergoes irreversible retreat, with current estimates

ranging from 1-4°C above pre-Industrial temperatures (1). Improved estimates of GrIS loss

for a given local or global temperature increase during past warm periods will thus provide

a critical constraint on this threshold. For the AIS, the key challenge involves determining

which marine-based sectors are most vulnerable to collapse, and identifying the forcing

(atmospheric or oceanic) that would trigger such events. Paleo-constraints on past ice-

sheet mass loss and forcings will be of particular value for validation of coupled ice sheet-

climate models.

Recommendations:

Addressing outstanding questions and challenges regarding rates, magnitudes, and

sources of past polar ice-sheet loss and resulting sea-level rise will continue to require

integration of ice-sheet, sea-level, and solid Earth geophysical studies with good spatial

distribution of well-dated RSL records to capture the magnitude of RSL variability across

the globe. Such synoptic analyses will need a sufficiently sophisticated cyberinfrastructure

to enable data sharing, transparency, and standardization of sea-level and ice-sheet paleo

data that are derived from multiple and diverse sub-disciplines. Where sufficiently

resolved, such data can then be used to identify sources of meltwater through their sea-

level fingerprints and refine estimates of GMSL change (103, 106). Near-field records of ice-

sheet extent and climate will also be essential in identifying the sources and forcing

mechanisms responsible for sea-level change. Most importantly, transcending conventional

paradigms of sea-level reconstructions and adopting the concept of geographic variability

imparted by dynamic physical processes will continue to lead to significant advances in our

understanding of GMSL rise in a warming world.

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Acknowledgments: This manuscript was developed based on collaborations and discussions that have stemmed from the PALSEA and PALSEA2 working group, presently funded by PAGES and INQUA. We thank four anonymous reviewers for comments that helped to improve the manuscript, A. Kemp for assistance with one of the figures, and A. Rovere, B. Honisch for helpful comments. Funding was provided by NSF awards #1155495 to AD, #1202632 to MER, #1343573 to AEC, #0958417 and #1043517 to PUC, OCE1458904 to BPH, and NERC Grant NE/I008675/1 to AJL.

Text Box 1. Methods of Reconstructing Past Sea Level and Ice Volume

Sea-level reconstructions: In our analysis of sea-level reconstructions, we consider two

categories separately: those that are derived from δ18O of marine carbonates (hereafter

termed δ18O-proxy records) and those based on direct observational evidence of sea level

or shoreline elevation (hereafter termed coastal records).

There are three types of δ18O-proxy records used to estimate former GMSL: (i)

benthic δ18O, which comprises a combined signal of temperature and global ice volume

(107), (ii) benthic or planktic δ18O in foraminifera or ostracods, paired with a proxy that

can independently constrain the temperature component embedded in this signal (31, 54),

(iii) planktic δ18O from evaporative marginal seas which is transformed into a RSL signal

using hydraulic models that constrain the salinity of surface waters as a function of sea

level (e.g., 56). Each of these geochemical approaches entails certain assumptions and

uncertainties, and we note that in the case of isolated basins such as the Red Sea or

Mediterranean (56, 108) additional corrections and assumptions about regional hydrology,

relative humidity, and tectonic stability and isostatic response of the sill depth must also be

made in addition to assumptions about how sea surface temperature changed.

Coastal records of former sea level reflect RSL rather than GMSL. Each RSL record

has uncertainties in its age and elevation that are primarily a function of the dating

technique(s) and the nature of the geologic archive, respectively. Coastal records include

geomorphological features, shallow-water corals, and salt-marsh records that directly track

the elevation of RSL through time. To associate changes in RSL to GMSL, one must quantify

and correct for geophysical processes (described below) that may contribute significantly

to RSL at the site (Fig. 1). Glacial isostatic adjustment (GIA) is arguably the most important

of these processes as it can influence the present-day elevation of sea-level indicators from

any time period in the past. Additional processes operate on more specific space and time

scales and thus only become important at those particular scales of analysis (Fig. 1). For

example, inter-annual to multi-decadal ocean-atmosphere interactions such as the North

Atlantic Oscillation or the Pacific Decadal Oscillation can cause RSL fluctuations of up to

several decimeters. Such processes are important when interpreting highly resolved

reconstructions such as those from instrumental records or from late-Holocene geologic

archives. On the other hand, dynamic topography resulting from flow in the Earth's mantle

can dominate the RSL signal over timescales of millions of years and produce high-

amplitude (meter- to multi-meter scale) variability.

Glacial isostatic adjustment (GIA): The water mass transfer between the ice sheets and

oceans during glacial-interglacial cycles causes changes in the Earth’s shape, gravity field,

and rotation that create a distinct spatial pattern to RSL across the globe (109) (Fig. 2).

These GIA processes dominate the spatial variability in sea-level change over millennial

time scales during the Quaternary and are also a significant (several mm yr-1) background

component to recent (historical) sea-level change (Fig. 2). GIA is also an important

contributor to RSL for older time periods due, in part, to the fact that the solid Earth is

continuing to isostatically adjust to the most recent deglaciation (18).

GIA models are primarily driven by an a priori ice model that defines the volume

and geographic extent of grounded ice through time, which is then used to solve for the

elevation of the shorelines and the changes in the height of the ocean floor and sea

surface—the latter being affected by changes in gravity. The ice model is constrained by

field evidence on the timing, thickness, and geographic extent of ice as well as by

constraints from observations of the elevation of RSL through time from sites close to

(“near-field”) and far from (“far-field”) the former ice sheets (e.g., 110, 111, 112). The other

key component of GIA models is an Earth model that is defined by layer thicknesses,

viscosity, elasticity and density of the Earth’s interior, which in turn dictate the way in

which the Earth’s surface responds and deforms to the assumed ice-load history. Typically

global GIA models are run using a single, laterally homogeneous Earth model. Regional

studies are often used to explore variations in the Earth model that provide a better fit to

data in that area. More recently, 3-D GIA models have been applied to examine the

influence of lateral Earth structure on RSL changes (e.g., 98, 113).

GIA models typically simulate global patterns in RSL change due to ice melting over

relatively short timescales (10s to 100s of years). In this case, the solid Earth response is

dominantly elastic and so accurately defining the viscosity structure, a primary source of

GIA model uncertainty, becomes less important. Since the elastic properties of the Earth

are relatively well defined from seismic investigations, the computed RSL response can be

accurately interpreted in terms of melt-source location. In other words, the spatial pattern

of RSL change can be used to ‘fingerprint’ melt sources, hence the use of the term ‘sea-level

fingerprinting’ for this application. This technique has been applied to rapid melting events

in the geological record (103, 106), 20th century sea-level change (114, 115) and regional

projections of future change (13, 116).

Dynamic topography: Lateral motion of the Earth’s tectonic plates (lithosphere) is due to

buoyancy driven viscous flow of the mantle that can also lead to vertical motion of the

Earth’s surface through plate convergence and consequent lithospheric deformation (e.g.,

orogenesis). However, the same viscous flow of the mantle also results in normal stresses

at the solid Earth-ocean/atmosphere interface, which can produce a vertical deflection of

this interface of up to a few km in amplitude (117-119). This component of the Earth’s

topography is associated with convectively supported vertical stresses and is termed

“dynamic topography.” (Note that the same term is also used in oceanography to described

undulations in the sea surface associated with flow within the ocean.) As the distribution of

density structure within the mantle evolves with time, so does the surface dynamic

topography, resulting in significant changes in both local RSL and GMSL on timescales of 1-

100 Ma (120-122). Vertical motion associated with dynamic topography also results in

lateral stresses that can cause significant crustal deformation and thus additional vertical

motion at the Earth’s surface (123, 124). This additional component of vertical motion has

yet to be considered in calculations of dynamic topography applied to sea-level studies.

Numerical models of mantle flow (e.g., 125) are used to compute dynamic

topography and predict how it evolves with time. The two primary inputs to these models

are a 3-D density anomaly field to drive the simulation of material flow in the mantle as

well as a radial viscosity profile that governs the rate of flow at a given depth in the mantle.

The 3-D density field is estimated from seismic models of the Earth’s internal velocity

structure, which reflects both thermal and chemical variations within the mantle. The

scaling from seismic velocity structure to density structure is not straightforward as it

involves assumptions regarding the cause of seismic velocity variations (thermal, chemical

or both; 120, 121). It is this uncertainty in defining the input density structure, as well as

our relatively poor knowledge of the Earth’s viscosity structure, that limits the accuracy of

modeled sea-level changes due to variations in dynamic topography.

Ice sheets: Ice-sheet reconstructions are informed primarily by direct observations of ice-

margin and thickness data and nearby marine sediment and RSL records. Ice-rafted debris

(IRD) and sediment provenance from geochemical analyses in marine cores are

particularly useful for extending ice-sheet reconstructions farther back in time beyond the

last deglaciation (i.e., >21 ka).

FIGURES

Figure 1. Stacked benthic 18O with time periods discussed in text. Benthic 18O

(green curve--LR04; ref. 32) provides a combined signal of ice volume and temperature

deep into the geologic past (107). Physical processes that contribute to RSL signals (blue

bars): length of blue bars indicates timespan over which the process is active; shading

denotes time interval where the process can have the most significant influence on RSL

reconstructions. For example, the rates of dynamic topography are slow enough that it

generally is only a significant factor for reconstructing older paleoshorelines, as denoted by

shading. GIA can dominate spatial variability in RSL across all of these timescales.

Figure 2. Selected Holocene relative sea-level (RSL) reconstructions. Elevations and

interpretation of sea-level index points (including errors) have not been amended from the

original publication. Radiocarbon ages were converted to calibrated dates where

necessary, shown as calibrated years before present x 1000 (kyr BP). (A-I) Site locations

and data sources are listed in Table S1. (I) GIA-adjusted sea level at North Carolina relative

to a pre-Industrial average for 1400-1800 C.E. Center panel (J) shows rates of present sea-

level change due to GIA, based on ICE-5G (126) and the VM2 Earth model with a 90-km

thick lithosphere.

Figure 3. Compilation of MIS 5e reconstructions for peak GMSL, GrIS contribution,

and best estimate of the total sea level budget. Estimates of (A) peak MIS 5e GMSL and

(B) meltwater contribution from the GrIS shown in chronological order of time of

publication from left to right. Ranges indicated by vertical bars; point estimates and best-

estimates within ranges shown as circles. GIA-corrected records are shown in red squares.

Horizontal dashed lines denote range of agreement between recent studies. (C) Total sea

level budget of MIS 5e, shown with estimated uncertainty for each component. One meter is

attributed to thermal expansion and loss of mountain glaciers (gray shading). As the

estimate of GrIS (green shading) has decreased, the overall peak SL estimate has grown,

leading to increased confidence of a more substantial contribution from the AIS (blue

shading). Data sources listed in Table S2.

Figure 4. Peak global mean temperature, atmospheric CO2, maximum GMSL, and

source(s) of meltwater. Light blue shading indicates uncertainty of sea level maximum.

Black vertical lines represent GMSL reconstructions from combined field observations and

GIA modeling; gray dashed lines are 18O-based reconstructions. Red pie charts over

Greenland and Antarctica denote fraction (not location) of ice retreat. Although the peaks

in temperature, CO2, and sea level within each time period may not be synchronous and ice

sheets are sensitive to factors not depicted here, note that significantly higher sea levels

were attained during MIS 5e and 11 when atmospheric CO2 forcing was significantly lower

than present. See Tables S3-S4 for data and sources.

Supplementary Materials:

www.sciencemag.org Figure S1 Tables S1 – S5 References (127-171)

Supplementary Materials for

Sea-level rise due to polar ice-sheet mass loss during past warm periods

A. Dutton, A. E. Carlson, A. J. Long, G. A. Milne, P. U. Clark, R. DeConto, B. P. Horton, S. Rahmstorf, M. E. Raymo

correspondence to: adutton@ufl.edu

This PDF file includes:

Figure S1 Tables S1 to S5

Figure S1.

Compilation of estimates of ice volume during the LGM (MIS 2) shown in chronological order of publication from left to right. Models of LGM ice volume draw upon the same observational datasets, hence the variability in GIA-based LGM ice volume estimates over time reflect the evolution of the modeling as well as differing interpretations of the observational data. Data sources listed in Table S5. Note that site-specific RSL positions of the LGM cluster near 120 m below present sea level where as many recent GMSL estimates from GIA models cluster in the range of 130-134 m.

Table S1.

Data sources for Holocene sea level reconstructions in Figure 2.

Figure Panel

Location Study Year Source

A Disko Bugt, Greenland Long et al. 2006 (127)

B New Jersey, USA Horton et al. 2013 (128)

C The Netherlands Hijma & Cohen 2010 (129)

D Yangtze Delta, China Zong 2004 (130)

E SW South Africa Compton 2001 (91)

F Christmas Island Woodroffe et al. 2012 (131)

G Patagonia, Argentina Rostami et al. 2000 (92)

H Orpheus Island, Australia Lambeck 2002 (132)

I North Carolina, USA Kemp et al. 2011 (81)

Table S2.

Data sources for MIS 5e peak sea level (1-14) and for meters of equivalent sea level contribution

from the Greenland Ice Sheet (15-28) shown in Figure 3.

Figure Source #

Study Year Bibliography number

1 Veeh 1966 (133)

2 Chappell and Shackleton 1986 (134)

3 Chen et al. 1991 (72)

4 Stirling et al. 1998 (57)

5 Muhs et al. 2002a (135)

6 Muhs et al. 2002b (136)

7 Hearty et al. 2007 (73)

8 Blanchon et al. 2009 (71)

9 Thompson et al. 2011 (74)

10 Kopp et al. 2009 (62)

11 Dutton and Lambeck 2012 (61)

12 O'Leary et al. 2013 (64)

13 Kopp et al. 2013 (77)

14 Dutton et al. 2015 (63)

15 Cuffey and Marshall 2000 (137)

16 Huybrechts 2002 (138)

17 Tarasov and Peltier 2003 (139)

18 L'homme et al. 2005 (140)

19 Otto-Bleisner et al. 2006 (141)

20 Oerlemans et al. 2006 (142)

21 Robinson et al. 2011 (143)

22 Colville et al. 2011 (67)

23 Fyke et al. 2011 (144)

24 Born and Nisancioglu 2012 (145)

25 Quiquet et al. 2013 (146)

26 Dahl-Jensen et al. 2013 (60)

27 Helsen et al. 2013 (147)

28 Stone et al. 2013 (148)

Table S3. Tabulated data that is depicted in Figure 4.

Present MIS 5e MIS 11 Pliocene

Age 2014 A.D. ~125 ka ~400 ka ~3.3 Ma

Global mean temperature (°C) (1) 1 (3) ~1 (7) 1 to 2? (12) 1.9 to 3.6 (16)

Arctic temperature (°C) (1) 2 (4) 4 to 8 (8) 4 to 9 (13) 4 to 11 (17)

Antarctic temperature (°C) (1) ? (5) 4 to 5 (9) 2 to3 (14) ?

Peak Atmospheric CO2 (ppm) 397 (5) 287 (10) 286 (10) 350 to 450 (18)

Peak sea level (m) (2) 0 (6) 6 to 9 (11) 6 to 13 (15) >6 (19)

Bold = data; Normal font = data and modeling; Italics = hypothesized

Footnotes:

(1) Temperatures are rounded to the nearest degree and reported relative to the pre-Industrial period. Please refer to primary sources for definitions of the pre-Industrial baseline in each study.

(2) Sea level is rounded to the nearest meter, and reported relative to the pre-Industrial period.

(3) Observed global mean land-ocean surface temperature; from Figure SPM1a in Ref. (149). (4) For the area 60-90 °N, relative to 1900 AD, Ref. (150); Data from the CRUTEM4v dataset, which is

available at www.cru.uea.ac.uk/cru/data/temperature/. (5) Instrumental data do not extend to pre-industrial period, and there is low confidence in trends since

the late 1950s (79).

(5) Globally averaged marine surface annual mean data, observed in 2014 Ref. (151). (6) Present global mean sea level is rounded to the nearest whole number.

(7) Global mean land-ocean surface temperature; Ref. (58, 68, 152) (8) Refs (59, 60, 153).

(9) Antarctic ice cores, Ref. (153) (10) Antarctic ice cores, Ref. (39) (11) Refs. (61-64, 77) and this study (12) Refs (36-38). (13) Refs. (40, 41). Based on only 2 records; data is much more limited than for MIS 5e.

(14) Antarctic ice core, Ref. (42). (15) Ref. (51-53)

(16) Ref. (16) (17) Ref. (17) Data from 5 sites.

(18) Refs (14, 15). (19) Hypothesis from this study.

Table S4. Sources of sea level data shown in Figure 4.

Source notation in figure

Study Year Bibliography number

K09 Kopp et al. 2009 (62)

DL12 Dutton and Lambeck 2012 (61)

O13 O'Leary et al 2013 (64)

D15 Dutton et al. 2015 (63)

G12 Grant et al. 2012 (65)

SR09 Sosdian and Rosenthal 2009 (31)

E12 Elderfield et al. 2012 (54)

RM12 Raymo and Mitrovica 2012 (51)

R12 Roberts et al. 2012 (52)

C15 Chen et al. 2014 (53)

R09 Rohling et al. 2009 (55)

M12 Miller et al. 2012 (24)

Table S5. Data sources for figure S1.

Source # Study Year Bibliography number

1 Broecker and Van Donk 1970 (154)

2 CLIMAP 1976 1976 (155)

3 CLIMAP 1981 1981 (156)

4 Chappell and Shackleton 1986 (134)

5 Nakada and Lambeck 1988 (157)

6 Fairbanks 1989 (158)

7 Tushingham and Peltier 1991 (112)

8 Peltier 1994 (159)

9 Hanebuth et al 2000 (160)

10 Yokoyama et al 2001 (161)

11 Yokoyama et al. 2000 (162)

12 Lambeck and Chappell 2001 (163)

13 Clark and Mix: EPILOG 2002 (164)

14 Lambeck et al. 2002 (165)

15 Milne et al. 2002 (166)

16 Peltier 2002 (167)

17 Peltier 2004 (126)

18 Peltier and Fairbanks 2006 (168)

19 Hanebuth et al. 2009 (169)

20 Clark et al. 2009 (170)

21 Clark et al. 2012 (171)

22 Austermann et al. 2013 (98)

23 Lambeck et al. 2014 (82)

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